Predicting the specific heat capacity of alumina/ethylene glycol nanofluids using support vector regression model optimized with Bayesian algorithm
Nanofluids are now considered the most essential constituent of solar thermal collector due to their superior thermal performance over conventional fluids. An accurate determination of the thermal efficiency of the solar collector depends on the value of the specific heat capacity of the nanofluid. So far...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/81784/1/20201028%20-%20Predicting%20the%20specific%20heat%20capacity%20of%20alumina_ethylene%20glycol%20nanofluids%20using%20support%20vector%20regression%20model%20optimized%20with%20Bayesian%20algorithm%20.pdf http://psasir.upm.edu.my/id/eprint/81784/ https://www.sciencedirect.com/science/article/abs/pii/S0038092X19301860 |
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http://psasir.upm.edu.my/id/eprint/81784/1/20201028%20-%20Predicting%20the%20specific%20heat%20capacity%20of%20alumina_ethylene%20glycol%20nanofluids%20using%20support%20vector%20regression%20model%20optimized%20with%20Bayesian%20algorithm%20.pdfhttp://psasir.upm.edu.my/id/eprint/81784/
https://www.sciencedirect.com/science/article/abs/pii/S0038092X19301860